[1/11] Scotland held its first Tokenisation Summit on 27 May at the University of Edinburgh.
The organisations in the room manage around £15 trillion between them.
Here is what happened, and what we are doing next. 🧵 @blockchain_scot
The OpenClaw ecosystem has a discoverability problem
ClawHub is great for finding agentic skills, but there's a tonne of high-quality adjacent apps that fly under the radar
We aim to fix this with ClawIndex
Submit legitimate projects for free and we'll add them to the portal
We also offer a verification process; a human quality review that earns projects a verification checkmark for additional assurance
We have many more plans for this discoverability tool, so it'll be an iterative process and we welcome any constructive feedback
Please retweet so we can index a more complete ecosystem
Link to website in next post below
14 years ago, in the basement of a Glasgow pub, I witnessed Lana Del Rey sing Video Games to a crowd of strangers
Now, in the same city, a stadium sings it back
AI PROMPTING → AI VERIFYING
AI prompting scales, because prompting is just typing.
But AI verifying doesn’t scale, because verifying AI output involves much more than just typing.
Sometimes you can verify by eye, which is why AI is great for frontend, images, and video. But for anything subtle, you need to read the code or text deeply — and that means knowing the topic well enough to correct the AI.
Researchers are well aware of this, which is why there’s so much work on evals and hallucination.
However, the concept of verification as the bottleneck for AI users is under-discussed. Yes, you can try formal verification, or critic models where one AI checks another, or other techniques. But to even be aware of the issue as a first class problem is half the battle.
For users: AI verifying is as important as AI prompting.